In-silico Study of Phytoconstituents from Tribulus terrestris as potential Anti-psoriatic agent

 

Ravindra Gaikwad¹*, Sanket Rathod², Anilkumar Shinde¹

¹Department of Pharmaceutics, Bharati Vidyapeeth College of Pharmacy, Kolhapur 416013, Maharashtra, India.

 

ABSTRACT:

Introduction: Psoriasis (Ps) is a well-known chronic non-infectious, inflammatory skin disease affecting about 2–3% of the worldwide Population. Pathogenesis includes the environmental trigger factors with other factors like genetic factors, trauma, chemicals, bacterial infection etc. Currently there is no drug which can permanently cure the skin lesions as well as completely eradicate this dermatosis. The purpose of this research is to investigate the anti-psoriatic activity of phytoconstituents of Tribulus terrestris by predicting the ligand-receptor binding and by predicting the ADMET parameters using Lipinski's rule. Methodology: The process of research work starts with protein and ligand structure preparation. Further docking was done using PyRxAutodock Vina. Afterward, analysis and visualisation of the interaction between protein-ligands was done, and ADMET profiling was carried out according to lipinski's rules using Swiss ADME. Result: we selected four phytoconstituents of Tribulus terrestris. Molecular docking simulation showed all four compounds had better binding affinities. Based on the results of prediction of ADMET values using the Lipinski rule, compound that are thought to have good activity. Conclusion: Based on results these molecules have discovered that they may be able to produce anti-psoriatic activity and found that they have a lower toxicity, and ADME analysis determined the easily absorbability to the tissue site. Hence, these compounds can be analysed by further in vitro studies and can be a leader in the designing of the potential drug for the psoriasis management.

 

 

 

1. INTRODUCTION:

Tribulus terrestris is commonly known as Gokshur or Gokharu or puncture vine family Zygophyllaceae. This plant is used in Indian and Chinese systems for the management of various kinds of diseases and disorders. The genus Tribulus contains almost 25 species¹. The Tribulus terrestris plant has a great interest in medicinal chemistry and shows diverse pharmacological activities, such as anti-cancer², anti-HIV³, antifungal⁴, antibacterial⁵, and anti-psoriatic activity⁶.

 

 

Tribulus terrestris possesses important secondary metabolites like saponins, polyphenolic compounds, Flavonoids, and alkaloids⁷. By doing literature survey we identified various phytocompounds of Tribulus terrestris from all of them alkaloidal phytoconstituents was used to investigate the antipsoriatic activity of plant. Psoriasis (Ps) is a well-known chronic non-infectious, inflammatory skin disease affecting about 2–3% of the worldwide Population⁸ which is characterized by an acute exanthematous plaque bearing large adherent, silvery scales^8,9. It is an autoimmune disease which is triggered by an activated cellular immune system⁹. Psoriasis categorized into five types like plaque, guttate, inverse, pustular, and erythrodermic. Plaque psoriasis is main type of it majority of peoples suffer from the same^10,11. In case of plaque psoriasis there is increased mitotic activity in the stratum corneum basal layer leads to the abnormal keratinization and elevation of the dermal papillae on the skin which results in a stratum corneum that desquamates and produces large silvery flakes^11,12. Pathogenesisis a complex interaction among the genetic, immunological, and environmental components. Tumor necrosis factor α, dendritic cells, and T-cells all contribute substantially to its pathogenesis. In early-onset psoriasis (beginning before age 40 years), carriage of HLA-Cw6 and environmental triggers, such as β-hemolytic streptococcal infections, are major determinants of disease expression¹³. The major treatments used to treat psoriasis include topical agents, photo therapies, and systemic treatments including treatment with methotrexate, cyclosporine, retinoid, and corticosteroids¹⁰. The major difficulty related to using these drugs is they may show to augmented some side effects. Usually, herbal medicines are predominant over allopathic drugs in the treatment of skin diseases due to increased activity and lesser side effects¹⁴.

 

Computer-Aided Drug Design (CADD) provides a valuable method in lead identification and optimization and it is cost-effective and less time consuming technique of drug discovery¹⁵. The structure-based drug design (SBDD), ligand-based drug design (LBDD) and sequence-based approaches are commonly used computational drug discovery approaches¹⁶. Molecular docking analysis using computational techniques is one of the most basic and important strategy used for drug discovery¹⁷. The docking studies helps to predict the most possible type of interaction of protein with ligand, the binding affinities, and the docking studies also orientations of the docked ligands at the active site of the target protein¹⁸. In this work anti-psoriatic activity of alkaloidal phytoconstituents of Tribulus Terrestris was investigated by using in silico technique. Active phytochemical compounds were selected from previously published literature⁷ and predicted their anti-psoriatic activity with the help molecular docking technique against spleen protein kinase (SPK), interleukin-23 (IL-23), Janus kinase (JAK-3), and Tumour necrosis factor α (TNFα). Furthermore, the drug-likeness and ADMET properties of those selected phytochemical compounds were also evaluated.

 

2. MATERIAL AND METHOD:

2.1. Software and hardware:

We used PubChem database (https://pubchem.ncbi.nlm.nih.gov/) (RRID:SCR_004284), RCSB Protein Data Bank (https://www.rcsb.org/) (RRID:SCR_012820), online tools such as ADMETlab 2.0 andSwissADME¹⁹. Using software like PyRxAutoDockVina0.8²⁰ else using protein visualizer BIOVIA Discovery Studio (RRID:SCR_015651)²¹.

 

2.2. In silico docking studies:

2.2.1. Protein structures:

The crystal structures of SPK (PDB—4XG6), IL-23 (PDB—3QWR), JAK-3 (PDB—5TTS), and TNF-α (PDB—2AZ5) were retrieved from RCSB Protein Data Bank (PDB) (https://www.rcsb.org/) for docking studies²². Preparation of selected protein is a process by which macromolecular structure of protein is converted into more suitable form to perform a computational experiment²³. Prior to performing molecular docking, it is necessary to clean and superimpose the protein²⁴ as well as energy minimization is also the key step in protein preparation as it removes the poor contact in the protein structure and remove the conformational error in PDB structured protein²⁵. The bound ligand, water and co-crystallized ligand were omitted with the help of BIOVIA Discovery Studio. BIOVA Discovery Studio 2017also used to find the binding site of our desire protein²³.

 

2.2.2. Ligand structures:

The 3D Structure of phytoconstituents of the Tribulus terrestris were retrieved from PubChem database (https://pubchem.ncbi.nlm.nih.gov/) was prepared and the energy was minimized and bond angle was optimized for each ligand as per the lead optimization requirements^24,26. There are 4 ligand (natural compounds) which were used for the docking energy analysis and pharmacokinetics analysis. The selected active constituents of the plant referred from previously published articles in renowned journals⁷.

 

 

 

Table 1. List of 4 phytoconstituents of Tribulus terrestrisalong with their molecular formula, PubChem CID, and structure.

Ligand	Molecule PubChem CID	Molecular Formula	Structure
Harmaline	3564	C13H14N2O
Harmalol	3565	C12H12N2O
Harman	5281404	C12H10N2
Harmine	5280953	C13H12N2O

 

 

2.2.3. Docking:

Molecular docking is a relatively fast, economical and widely used computational technique for predicting in silico binding modes as well as affinities of molecular recognition events²⁷. A molecular docking was performed to investigate the probable mode of action of selected ligand molecules for anti-psoriatic potentialall the target proteins were done using PyRx soft ware which uses improved functions of Autodock Vina²⁰. The SDF file of ligands were converted to pdbqt file format and flexible docking was carried. Further more receptor grid was generated after selection of the active site of protein by using the PyRx software²³. The Vina Search Space i.e.grid center and dimensions between ligand and target protein atoms are provided in Table 2. Each ligand molecule were docked separately with the all four macromolecules. Final docked conformations were downloaded in the PDB format and saved for further investigation. BIOVIA Discovery Studio were used for detailed visualization and comparison of the docked sites of Harmaline, Harmalol, Harman, Harmine with all target protein molecules²¹. The final result of each docked molecule to protein appears in terms of final minimum score which is also referred as dock score interaction/docking energy of receptor-ligand²⁸.

 

2.3. Drug-likeness and ADMET proiling:

It is very important to evaluate the Drug-likeness and ADMET profile of selected compounds earlier to avoid waste of time/resources²⁹. In silico Swiss ADME (http://www.swissadme.ch/) was used to determine the drug-likeness properties of the selected ligand molecules, that is, Molecular weight (MW≤500 Dalton), octanol–water partition coefficient (iLOGP), number of hydrogen donors (HBD≤5), number of hydrogen acceptors (HBA≤10), Topological Polar Surface Area (TPSA), number of rotatable bonds (nROT)^19,30. Swiss ADME is an online in silicotool which is used for the determining the drug like properties of the selected ligand molecules by uploading SDF file of ligand and then conversion of structure into Smiles of ligand was done which is then followed further by the command to run this file. After applying the run command, all the properties of uploaded ligand appears on screen. The important molecular properties based on Lipinski Rules of five (RO5)²⁵.

 

3. RESULT AND DISCUSSION:

The molecular docking analysis of all selected four natural compounds of Tribulus terrestrisplant accompanied with the help of flexible or blind docking method. PyRx virtual screening tool (Auto Dock Vina) was used to determine the molecular docking studies of the selected protein. The molecular docking results of ligands with SPK (PDB—4XG6), IL-23 (PDB—3QWR), JAK-3 (PDB—5TTS), and TNF-α (PDB—2AZ5) proteins containing binding energy (Kcal/mol) is shown in Table 3. After docking of the inhibiting ligands the protein-ligand interaction molecule, the ligands with proteins with SPK (PDB—4XG6), IL-23 (PDB—3QWR), JAK-3 (PDB—5TTS), and TNF-α (PDB—2AZ5) reveals that all the ligands binding active sites occupy active pockets of the proteins as shown in Fig. 1-4. In these protein-ligand interactions studies which is shown in Table 3 describes, anti-psoriatic target protein and the which type of interaction is shown in between protein-ligand from which resolve the important riddle for which residues are substantial for protein stabilization as well as otherwise important residue which are important for the protein conformation alteration²⁵. Protein-ligand Docked complex and their binding affinity generated through molecular docking method, Interacting residues and interaction type are shown in Table 3.

 

 

Table 2. Grid center and dimensions between ligand and target protein atoms.

 

Table 3. Protein-ligand Docked complex and their binding affinity generated through molecular docking method, Interacting residues and interaction type.

Protein-ligand Docked complex	Binding affinity (kal/mol)	Interacting residues	Interaction type
SPK_Harmaline	-7	LEU 377, PHE 382, VAL 385, ALA 400, LYS 402, MET 448, MET 450, ALA 451, GLY 454, PRO 455, LEU 501, ASP 512	van der Waals, π -Sigma, π-Sulfur, Alkyl, π-Alkyl
SPK_Harmalol	-7.1	LEU 377, PHE 382, VAL 385, ALA 400, LYS 402, MET 448, MET 450, ALA 451, GLY 454, PRO 455, LEU 501, ASP 512	van der Waals, Conventional Hydrogen Bond, π-Sigma, π-Sulfur, Alkyl, π-Alkyl
SPK_Harman	-6.8	LEU 377, PHE 382, VAL 385, ALA 400, LYS 402, GLU 420, MET 448, GLY 454, PRO 455,  LEU 501, ASP 512	van der Waals, π-Anion, π-Sigma, π-Sulfur, Alkyl, π-Alkyl
SPK_Harmine	-7	LEU 377, GLU 378, PHE 382, VAL 385, ALA 400, LYS 402, MET 448, MET 450, ALA 451, GLU 452, GLY 454, PRO 455,  LEU 501, SER 511, ASP 512	van der Waals, Carbon Hydrogen Bond, π-Anion, π-Sigma, π-Sulfur, Alkyl, π-Alkyl
IL 23_Harmaline	-6.8	TYR 114, GLU 181, ARG 208, TYR 246, PHE 247, SER 248, ASP 290, TYR 292, TYR 293	van der Waals, π - π Stacked
IL 23_Harmalol	-6.9	TYR 114, ALA 179, ALA 180, GLU 181, ARG 208, TRP 240, TYR 246, PHE 247, SER 248, ASP 290, ARG 291, TYR 292	van der Waals, Conventional Hydrogen Bond, π - π Stacked, π - π T-shaped, π -Alkyl
IL 23_Harman	-6.5	TYR 114, TYR 246, PHE 247, SER 248, ASP 290, TYR 292, TYR 293	van der Waals, Pi-Donor Hydrogen Bond, π - π Stacked, π - π T-shaped, π -Alkyl
IL 23_Harmine	-6.6	TYR 114, GLU 181, ARG 208, TYR 246, PHE 247, SER 248, ASP 290, TYR 292, TYR 293	van der Waals, π-Sigma, π - π Stacked, π - π T-shaped, π -Alkyl
Jak3_Harmaline	-7.6	LEU 828,VAL 836, ALA 853, LYS 855, VAL 884, MET 902, TYR 904, LEU 905, GLY 908, LEU 956, ALA 966, ASP 967	van der Waals, Carbon Hydrogen Bond, π-Sigma, Alkyl, π-Alkyl
Jak3_Harmalol	-7.8	LEU 828, VAL 836, ALA 853, LYS 855, VAL 884, MET 902, TYR 904, LEU 905, PRO 906, GLY 908, LEU 956, ALA 966, ASP 967	van der Waals, Carbon Hydrogen Bond,  π-Sigma, Alkyl, π-Alkyl
Jak3_Harman	-7.7	LEU 828, VAL 836, ALA 853, LYS 855, VAL 884, MET 902, TYR 904, LEU 905, GLY 908, LEU 956, ALA 966, ASP 967	van der Waals,  π-Sigma, Alkyl, π-Alkyl
Jak3_Harmine	-7.5	LEU 828, VAL 836, ALA 853, VAL 884, MET 902, GLU 903, TYR 904, LEU 905, PRO 906, GLY 908, LEU 956, ALA 966	van der Waals, π -Sigma, π-Sulfur, Alkyl, π-Alkyl
TNF α_Harmaline	-7	ARG B: 82 ARG D:82, VAL B:91, VAL D:91, ASN B:92, ASN D:92, LEU B:93, LEU D:93, PHE B:124, PHE D:124, GLN D:125	van der Waals, Alkyl, π-Alkyl
TNF α_Harmalol	-7	ARG D:82, VAL B:91, VAL D:91, ASN B:92, ASN D:92, LEU B:93, LEU D:93, PHE B:124, PHE D:124, GLN D:125, LEU D:126	van der Waals, Carbon Hydrogen Bond, Alkyl, π-Alkyl
TNF α_Harman	-7.2	LEU C:57, LEU D:57, TYR D:59, SER D:60, GLN D:61, TYR D:119, LEU D:120, GLY C:121, GLY D:121, GLY C:122, TYR D:151	van der Waals, π - π Stacked, π-Alkyl
TNF α_Harmine	-7.1	ARG D:82, VAL B:91, VAL D:91, ASN B: 92, ASN D:92, LEU B:93, LEU D:93, PHE B: 124, PHE D:124, GLN D:125	van der Waals, Alkyl, π-Alkyl

 

 

Fig. 1. Binding modes of the lig.1: Harmaline, lig.2: Harmalol, lig.3: Harman, lig.4: Harmine as interacted with SPK (PDB—4XG6) which is shown in center.

 

Fig. 2. Binding modes of the lig.1: Harmaline, lig.2: Harmalol, lig.3: Harman, lig.4: Harmine as interacted with IL-23 (PDB—3QWR) which is shown in center.

 

Fig. 3. Binding modes of the lig.1:Harmaline, lig.2:Harmalol, lig.3: Harman, lig.4:Harmine as interacted with JAK-3 (PDB—5TTS)which is shown in center.

 

Fig. 3. Binding modes of the lig.1:Harmaline, lig.2:Harmalol, lig.3: Harman, lig.4:Harmine as interacted with TNF-α (PDB—2AZ5)which is shown in center.

 

Table 4. List of pharmacokinetic properties (Physicochemical, drug likeness) of the selected 4 Ligand molecules.

Ligand	MW	iLOGP	HBD	HBA	TPSA	nRot	nHA	nAHA	MR	PAINS #alert	Brenk #alert	Bioavailability Score
Harmaline	214.26	2.11	1	2	37.38	1	16	9	69.23	0	0	0.55
Harmalol	200.24	1.58	2	2	48.38	0	15	9	64.76	0	0	0.55
Harman	182.22	1.75	1	1	28.68	0	14	13	58.57	0	0	0.55
Harmine	212.25	2.07	1	2	37.91	1	16	13	65.06	0	0	0.55

MW: Molecular weight, iLOGP: Octanol/water partition coefficient, HBD: Number of H-bond Donors, HBA: Number of H-Bond acceptors, TPSA: Topological Polar Surface Area, nRot: Number of Rotatable bonds, nHA: Number of heavy atoms, nAHA: Number of aromatic heavy atoms, MR: Molar refractivity.

 

 

All the selected four molecules have shown desired ADME properties, indicating their suitability as drug-like candidates. The ADME properties and Drug likeness property analysis of screened compounds is summarized in Table 4. Briefly, all of the four screened molecules followed Lipinski's rule of five concerning molecular weight (MW ˂500), number of hydrogen bond donors (HBD ≤5), number of hydrogen bond acceptors (HBA ≤10), octanol–water partition coefficient (iLOGP), and molar refractivity (MR 40-130). The bioavailability score was observed and results was summarized in Table 4.

 

4. CONCLUSION:

Currently, available treatment for psoriasis management has the disadvantages like serious adverse drug effects, long duration of action, and patient unacceptability. To search for an effective drug candidate is of prime importance nowadays. Herbs and herbal medicines come from a natural source having a wide variety of phytoconstituents with a wide range of pharmacological action. Tribulus Terrestris plant used since ancient times in the Indian and Chinese system of medicine for the management of a variety of diseases. Here an attempt has been made to apply in-silicomolecular docking study and ADME drug likeliness prediction was also carried out to screen ligands for drug-likeness; efficacy. In this in-silicomolecular dockingapproach, selected four phytoconstituents Pub Chem CID 3564, Pub Chem CID 3565, Pub Chem CID 5281404, Pub Chem CID 5280953 docked against SPK, IL-23, JAC-3, TNFα. Docking study showed that these selected four ligand molecules have a higher binding affinity ranging between −6.5and −7. 8kcal/mol with SPK, IL-23, JAC-3, TNFαproteins. Based on results these molecules have discovered that they may be able to produce anti-psoriatic activity and found that they have found a lower toxicity, and ADME analysis determined the easily absorbability to the tissue site. Hence, these compounds can be analysed by further in vitro studies and can be a leader in the designing of the potential drug in the management of psoriasis.

 

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Received on 08.04.2022       Modified on 24.04.2022

Accepted on 10.05.2022   ©Asian Pharma Press All Right Reserved

Asian J. Pharm. Res. 2022; 12(4):267-274.